code: def _feed_forward(c: FeedForwardConfigs):
      """
      Initialize a [feed forward network](feed_forward.html)
      """
      return FeedForward(
          c.d_model,
          c.d_ff,
          dropout=c.dropout,
          activation=c.activation,
          is_gated=c.is_gated,
          bias1=c.bias1,
          bias2=c.bias2,
          bias_gate=c.bias_gate,
      )
  
imports: import copy
  import torch.nn
  from labml.configs import BaseConfigs, option, calculate, aggregate
  from labml_helpers.module import Module
  from .feed_forward import FeedForward
  from .mha import MultiHeadAttention
  from .models import EmbeddingsWithPositionalEncoding, EmbeddingsWithLearnedPositionalEncoding, TransformerLayer, Encoder, Decoder, Generator, EncoderDecoder
label_desc: Use image node_id 3 for calling a global function with example usage: _feed_forward(c) and returns: FeedForward